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About The Role The role owns the design, implementation, and scaling of core data infrastructure, high-throughput ETL pipelines, and analytical data models that drive company-wide decision-making. The team works closely with data scientists, product managers, and analytics engineers to ensure data reliability, performance, and accessibility across all business units. Key Responsibilities Architect, build, and maintain scalable batch and streaming data pipelines using Python, SQL, and Apache Spark Manage cloud data warehousing infrastructure (Snowflake, BigQuery, or Redshift) with a focus on cost optimization and query performance Implement robust data quality checks, schema evolution handling, and monitoring tools to guarantee data integrity across all sources Collaborate with analytics and engineering teams to model data for reporting, machine learning features, and operational workflows Write clean, modular, and well-tested infrastructure-as-code using Terraform and CI/CD deployment pipelines Document data lineage, schemas, and pipeline architectures to foster a culture of data transparency and self-service What We Are Looking For 3–6 years of professional experience in data engineering, backend development, or analytics engineering roles Advanced SQL and Python programming skills, with proven expertise in building production-grade data pipelines Hands-on experience with modern cloud data warehouses (Snowflake, BigQuery) and orchestrators (Airflow, Dagster, Prefect) Solid understanding of distributed data processing frameworks such as Apache Spark, Flink, or Ray Bachelor's degree in Computer Science, Statistics, Engineering, or equivalent practical experience Bonus: Experience with real-time streaming technologies (Kafka, Kinesis) and data lakehouse formats (Iceberg, Delta Lake)
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.